{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Digit Classification</h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.image as mpimg\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "from yellowbrick.classifier import ClassificationReport, ConfusionMatrix, ROCAUC, ClassBalance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Loading the data</h2>\n",
    "\n",
    "<ul>\n",
    "<li>We use panda's read_csv to read train.csv into a dataframe</li>\n",
    "<li>Separate our images and labels for supervised learning.</li>\n",
    "<li>Use train_test_split to break data into sets for training and testing</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "labeled_images = pd.read_csv('train.csv')\n",
    "images = labeled_images.iloc[0:10000,1:].as_matrix()\n",
    "labels = labeled_images.iloc[0:10000,:1].as_matrix()\n",
    "labels = np.ravel(labels)\n",
    "train_images, test_images, train_labels, test_labels = train_test_split(images, labels, train_size=0.75, test_size=0.25, random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>Viewing an image</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1ce8d87e898>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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gORXuhre3t2vOnDnxbiNi4e6GX32cpNS5Gx7tf1c+n08tLS3Drh/xMryrq0tlZWVat26d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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ce87f5bc18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 5000\n",
    "img = train_images[i]\n",
    "img=img.reshape((28,28))\n",
    "plt.imshow(img, cmap='gray')\n",
    "plt.title(train_labels[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EEEJYIAVSCCGEsEAKpBBCCGGBFEghhBDCAimQQgghhAVSIIUQQggLpEAKIYQQ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ce864c5748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bayes = GaussianNB()\n",
    "classes = [0,1,2,3,4,5,6,7,8,9]\n",
    "visualizer = ClassificationReport(bayes, classes=classes)\n",
    "\n",
    "visualizer.fit(train_images, train_labels)\n",
    "visualizer.score(test_images, test_labels)\n",
    "g = visualizer.poof()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jlMep7IpXfqd5Kkb5npqqGPd/yrLiqXGM1ZhZbdQ4xurJXNapbLt9Krtq1arMnDnTXg8v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\nZhERERNRMYuIiJiIillERMRE/g/wnUuNhXSgtwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ce8c791390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bayes = GaussianNB()\n",
    "visualizer = ConfusionMatrix(bayes)\n",
    "\n",
    "visualizer.fit(train_images, train_labels)\n",
    "visualizer.score(test_images, test_labels)\n",
    "g = visualizer.poof()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jR45U/fr1FRwcrFmzZlW5vCaaN2+up59+Wr/73e9kjFFISIiWLVvGzPgG4TCXHocCAADX\nHIesAQCwAIUMAIAFKGQAACxAIQMAYIGAnWXt8XhUXFys0NDQiz7jCQDA9cgYo7KyMoWFhXmvcfBd\nASvk4uJi7d27N1CbBwAgIGJiYiq9+mDACvnCVXxiYmJ8dmGBq1FQUHDZhfNtVVey1pWcEln9pa5k\nrSs5JbL6SyCylpaWau/evVVexS5ghXzhMLXT6VS9evUCkiFQ262NupK1ruSUyOovdSVrXckpkdVf\nApW1qj/TXrGQKyoqNHXqVB04cEAOh0NPPfWU6tWrp/T0dDkcDjVv3lwzZsxQUFCQVq1apezsbIWE\nhGj8+PFKSEjw+R0BAOB6dMVCvnAN4OzsbG3fvl3PPvusjDFKTU1Vhw4dNH36dG3cuFGtW7dWVlaW\n1qxZI7fbreTkZMXHxwfkcDQAAHXNFQu5e/fu6tatmyTpq6++UmRkpLZt2+a9+H2XLl20detWBQUF\nqU2bNnI6nXI6nYqOjlZhYWGlX30GAAAuVqPPIYeEhGjSpEnei7lf+Jo26fz33Z49e1Yul+uis8bC\nwsIu+3o+AABQuav6conjx48rKSlJLpdLubm5kqQNGzZo27Ztio+P1/vvv6+ZM2dKOv8NKePGjfN+\nefyl3G63CgoKvv89AACgDmnVqlWlJ5Rd8ZD1m2++qaKiIo0dO1YNGjSQw+FQq1attH37dnXo0EE5\nOTm69957FRsbq0WLFsntdqu0tFT79u1TTExMrYP5W15enuLi4q75dmujrmStKzklsvpLXclaV3JK\nZPWXQGS90kT0ioXcs2dPTZ48WcOGDVN5ebmmTJmin/3sZ5o2bZoWLlyoZs2aKTExUcHBwUpJSVFy\ncrKMMUpLS6tTp78DABBIVyzkhg0bavHixZctX7ly5WXLkpKSlJSU5JtkAADcQPhyCQAALEAhAwBg\nAQoZAAALUMgAAFiAQgYAwAIUMgAAFqCQAQCwAIUMAIAFKGQAACxAIQMAYAEKGQAAC1DIAABYgEIG\nAMACFDIAABagkAEAsACFDACABUICHQAAbjQvbUm/qvV3bXm9RuuN7DS3NnFgCWbIAABYgEIGAMAC\nFDIAABagkAEAsACFDACABTjLGleUG17zp0luDde7x1VeuzAAcJ1ihgwAgAUoZAAALEAhAwBgAQoZ\nAAALUMgAAFiAQgYAwAIUMgAAFqCQAQCwAIUMAIAFuFJXgPjj+1D5LlQAqLuYIQMAYAEKGQAAC1DI\nAABYgEIGAMACFDIAABagkAEAsACFDACABShkAAAsUO2FQcrKyjRlyhQdOXJEpaWlGj9+vG699VaN\nHTtWP/3pTyVJQ4cO1f33369Vq1YpOztbISEhGj9+vBISEq5FfgAArgvVFvL69esVFRWl+fPn65tv\nvlG/fv00YcIE/fa3v9WoUaO86x0/flxZWVlas2aN3G63kpOTFR8fL6fT6fc7AADA9aDaQu7Vq5cS\nExMlScYYBQcHq6CgQAcOHNDGjRvVpEkTTZkyRTt37lSbNm3kdDrldDoVHR2twsJCxcbGXpM7AQBA\nXVdtIYeFhUmSXC6XHn30UaWmpqq0tFSDBg1Sq1attGzZMr3wwgtq0aKFIiIiLrqdy+WqUYCCgoLv\nEf/7ycvLC9i2/aEu3R8bstqQoabI6nt1JefVsOE+2ZChpmzLesUvlzh69KgmTJig5ORk9enTR2fO\nnFFkZKQkqUePHsrIyFC7du1UXFzsvU1xcfFFBV2dVq1aqV69erWMX3t5eXmKi4u75tu9oCZfFnG1\n/HV/cv0wpr+yvhI81OdjJle86vMxr0agn6tXo65kDXROf7z+Jf+9rmoq0Pv1agQiq9vtrnYSWu1Z\n1idOnNCoUaP0+OOPa+DAgZKk0aNHa+fOnZKkDz74QC1btlRsbKzy8vLkdrt19uxZ7du3TzExMT68\nGwAAXN+qnSFnZmbqzJkzWrp0qZYuXSpJSk9P1+zZsxUaGqof/vCHysjIUHh4uFJSUpScnCxjjNLS\n0gIy6wUAoK6qtpCnTp2qqVOnXrY8Ozv7smVJSUlKSkryXTIAAG4gXBgEAAALUMgAAFjgimdZAwBu\nXLnhV1cTNflUxj2u8tqFuc5RyACqNS/3s6tYO1IbarD+pHua1z4QcJ2ikAEA14WrvQ7Bnhqscy2v\nQ3BdFXLw77Ou7gavfFqj1Sr+mFKLNAAA1BwndQEAYAEKGQAAC1DIAABY4Lr6GzJQVxR+WPOXXpik\nwg9rtm6Le/k4CVBXMUMGAMACzJABXDeu6pMWfMoClmGGDACABShkAAAsQCEDAGABChkAAAtQyAAA\nWIBCBgDAAhQyAAAWoJABALAAhQwAgAUoZAAALEAhAwBgAQoZAAALUMgAAFiAQgYAwAIUMgAAFqCQ\nAQCwAIUMAIAFKGQAACxAIQMAYAEKGQAAC1DIAABYgEIGAMACFDIAABagkAEAsACFDACABShkAAAs\nQCEDAGABChkAAAtQyAAAWCCkul+WlZVpypQpOnLkiEpLSzV+/HjdfvvtSk9Pl8PhUPPmzTVjxgwF\nBQVp1apVys7OVkhIiMaPH6+EhIRrdR8AAKjzqi3k9evXKyoqSvPnz9c333yjfv36qUWLFkpNTVWH\nDh00ffp0bdy4Ua1bt1ZWVpbWrFkjt9ut5ORkxcfHy+l0Xqv7AQBAnVZtIffq1UuJiYmSJGOMgoOD\ntXv3brVv316S1KVLF23dulVBQUFq06aNnE6nnE6noqOjVVhYqNjYWP/fAwAArgPVFnJYWJgkyeVy\n6dFHH1VqaqrmzZsnh8Ph/f3Zs2flcrkUERFx0e1cLleNAhQUFNQ2+zWTl5cX6Ag1UldySmQN8/mI\n5/lnv0b6fMQb/fH3l7qSta7klK5t1moLWZKOHj2qCRMmKDk5WX369NH8+fO9vysuLlZkZKTCw8NV\nXFx80fLvFnR1WrVqpXr16tUieiVe+dQ341wiLi7O52Pu2vK6z8f0R05JyvXDmP7KuscPY/oja+GH\nPh9Skn+ybsj9zOdj+uvx98d7QF15/Uv+ycrr33dZ3W53tZPQas+yPnHihEaNGqXHH39cAwcOlCTd\neeed2r59uyQpJydH7dq1U2xsrPLy8uR2u3X27Fnt27dPMTExPrsTAABc76qdIWdmZurMmTNaunSp\nli5dKkl68sknNWvWLC1cuFDNmjVTYmKigoODlZKSouTkZBljlJaW5rtZLwAAN4BqC3nq1KmaOnXq\nZctXrlx52bKkpCQlJSX5LhkAADcQLgwCAIAFKGQAACxAIQMAYAEKGQAAC1DIAABYgEIGAMACFDIA\nABagkAEAsACFDACABShkAAAsQCEDAGABChkAAAtQyAAAWIBCBgDAAhQyAAAWoJABALAAhQwAgAUo\nZAAALEAhAwBgAQoZAAALUMgAAFiAQgYAwAIUMgAAFqCQAQCwAIUMAIAFKGQAACxAIQMAYAEKGQAA\nC1DIAABYgEIGAMACFDIAABagkAEAsACFDACABShkAAAsQCEDAGABChkAAAtQyAAAWIBCBgDAAhQy\nAAAWoJABALAAhQwAgAVqVMg7duxQSkqKJOnTTz9V586dlZKSopSUFP3P//yPJGnVqlXq37+/kpKS\ntGnTJv8lBgDgOhRypRVWrFih9evXq0GDBpKk3bt367e//a1GjRrlXef48ePKysrSmjVr5Ha7lZyc\nrPj4eDmdTv8lBwDgOnLFGXJ0dLSWLFni/bmgoECbN2/WsGHDNGXKFLlcLu3cuVNt2rSR0+lURESE\noqOjVVhY6NfgAABcT644Q05MTNThw4e9P8fGxmrQoEFq1aqVli1bphdeeEEtWrRQRESEd52wsDC5\nXK4aBSgoKKhF7GsrLy8v0BFqpK7klMga5vMRz/PPfo30+Yg3+uPvL3Ula13JKV3brFcs5Ev16NFD\nkZGR3v/OyMhQu3btVFxc7F2nuLj4ooKuTqtWrVSvXr2rjVG5Vz71zTiXiIuL8/mYu7a87vMx/ZFT\nknL9MKa/su7xw5j+yFr4oc+HlOSfrBtyP/P5mP56/P3xHlBXXv+Sf7Ly+vddVrfbXe0k9KrPsh49\nerR27twpSfrggw/UsmVLxcbGKi8vT263W2fPntW+ffsUExNT+9QAANxgrnqGPHPmTGVkZCg0NFQ/\n/OEPlZGRofDwcKWkpCg5OVnGGKWlpflu1gsAwA2gRoXcuHFjrVq1SpLUsmVLZWdnX7ZOUlKSkpKS\nfJsOAIAbBBcGAQDAAhQyAAAWoJABALAAhQwAgAUoZAAALEAhAwBgAQoZAAALUMgAAFiAQgYAwAIU\nMgAAFqCQAQCwAIUMAIAFKGQAACxAIQMAYAEKGQAAC1DIAABYgEIGAMACFDIAABagkAEAsACFDACA\nBShkAAAsQCEDAGABChkAAAtQyAAAWIBCBgDAAhQyAAAWoJABALAAhQwAgAUoZAAALEAhAwBgAQoZ\nAAALUMgAAFiAQgYAwAIUMgAAFqCQAQCwAIUMAIAFKGQAACxAIQMAYAEKGQAAC1DIAABYoEaFvGPH\nDqWkpEiSvvjiCw0dOlTJycmaMWOGPB6PJGnVqlXq37+/kpKStGnTJv8lBgDgOnTFQl6xYoWmTp0q\nt9stSZozZ45SU1P1yiuvyBijjRs36vjx48rKylJ2drZefPFFLVy4UKWlpX4PDwDA9eKKhRwdHa0l\nS5Z4f969e7fat28vSerSpYu2bdumnTt3qk2bNnI6nYqIiFB0dLQKCwv9lxoAgOtMyJVWSExM1OHD\nh70/G2PkcDgkSWFhYTp79qxcLpciIiK864SFhcnlctUoQEFBwdVmvuby8vICHaFG6kpOiaxhPh/x\nPP/s10ifj3ijP/7+Uley1pWc0rXNesVCvlRQ0P8/qS4uLlZkZKTCw8NVXFx80fLvFnR1WrVqpXr1\n6l1tjMq98qlvxrlEXFycz8fcteV1n4/pj5ySlOuHMf2VdY8fxvRH1sIPfT6kJP9k3ZD7mc/H9Nfj\n74/3gLry+pf8k5XXv++yut3uaiehV32W9Z133qnt27dLknJyctSuXTvFxsYqLy9PbrdbZ8+e1b59\n+xQTE1P71AAA3GCueoY8adIkTZs2TQsXLlSzZs2UmJio4OBgpaSkKDk5WcYYpaWl+W7WCwDADaBG\nhdy4cWOtWrVKktS0aVOtXLnysnWSkpKUlJTk23QAANwguDAIAAAWoJABALAAhQwAgAUoZAAALEAh\nAwBgAQoZAAALUMgAAFiAQgYAwAIUMgAAFqCQAQCwAIUMAIAFKGQAACxAIQMAYAEKGQAAC1DIAABY\ngEIGAMACFDIAABagkAEAsACFDACABShkAAAsQCEDAGABChkAAAtQyAAAWIBCBgDAAhQyAAAWoJAB\nALAAhQwAgAUoZAAALEAhAwBgAQoZAAALUMgAAFiAQgYAwAIUMgAAFqCQAQCwAIUMAIAFKGQAACxA\nIQMAYAEKGQAAC1DIAABYgEIGAMACFDIAABYIqe0NH3jgAYWHh0uSGjdurHHjxik9PV0Oh0PNmzfX\njBkzFBRE3wMAUBO1KmS32y1jjLKysrzLxo0bp9TUVHXo0EHTp0/Xxo0b1aNHD58FBQDgelarKWxh\nYaFKSko0atQoDR8+XPn5+dq9e7fat28vSerSpYu2bdvm06AAAFzPajVDrl+/vkaPHq1Bgwbp4MGD\nGjNmjIwxcjgckqSwsDCdPXu2RmMVFBTUJsI1lZeXF+gINVJXckpkDfP5iOf5Z79G+nzEG/3x95e6\nkrWu5JSubdZaFXLTpk3VpEkTORwONW3aVFFRUdq9e7f398XFxYqMrNmLuFWrVqpXr15tYlzulU99\nM84l4uLifD7mri2v+3xMf+SUpFw/jOmvrHv8MKY/shZ+6PMhJfkn64bcz3w+pr8ef3+8B9SV17/k\nn6y8/n2X1e12VzsJrdUh69WrV2vu3LmSpKKiIrlcLsXHx2v79u2SpJycHLVr1642QwMAcEOq1Qx5\n4MCBmjx5soYOHSqHw6HZs2fr5ptv1rRp07Rw4UI1a9ZMiYmJvs4KAMB1q1aF7HQ69cc//vGy5StX\nrvzegQAAuBHxQWEAACxAIQMAYAEKGQAAC1DIAABYgEIGAMACFDIAABagkAEAsACFDACABShkAAAs\nQCEDAGBuCOScAAAHR0lEQVQBChkAAAtQyAAAWIBCBgDAAhQyAAAWoJABALAAhQwAgAUoZAAALEAh\nAwBgAQoZAAALUMgAAFiAQgYAwAIUMgAAFqCQAQCwAIUMAIAFKGQAACxAIQMAYAEKGQAAC1DIAABY\ngEIGAMACFDIAABagkAEAsACFDACABShkAAAsQCEDAGABChkAAAtQyAAAWIBCBgDAAhQyAAAWoJAB\nALAAhQwAgAUoZAAALBDiy8E8Ho9mzpypPXv2yOl0atasWWrSpIkvNwEAwHXJpzPkDRs2qLS0VK+9\n9pp+//vfa+7cub4cHgCA65ZPZ8h5eXnq3LmzJKl169YqKCiocl1jjCSptLTUZ9u/NSzUZ2N9l9vt\n9vmYoY6GPh/THzklST++1edD+itryK2RPh/TH1k98v0+lfyTtb48Ph/TX4+/P94D6srrX/LTfuX1\n77OxLvTdhf67lMNU9ZtaePLJJ9WzZ0917dpVktStWzdt2LBBISGX9/7Zs2e1d+9eX20aAIA6ISYm\nRhEREZct9+kMOTw8XMXFxd6fPR5PpWUsSWFhYYqJiVFoaKgcDocvYwAAYB1jjMrKyhQWFlbp731a\nyG3bttWmTZt0//33Kz8/XzExMVWuGxQUVOm/EAAAuF7Vr1+/yt/59JD1hbOs9+7dK2OMZs+erZ/9\n7Ge+Gh4AgOuWTwsZAADUDhcGAQDAAhQyAAAW8OlJXXVBXbua2I4dO7RgwQJlZWUFOkqVysrKNGXK\nFB05ckSlpaUaP368fvnLXwY6VqUqKio0depUHThwQA6HQ0899VS1Jx8G2smTJ9W/f3/9+c9/tvp8\njAceeEDh4eGSpMaNG2vOnDkBTlS15cuX691331VZWZmGDh2qQYMGBTpSpdauXas33nhD0vnPwv7z\nn//U1q1bFRnp+8/afh9lZWVKT0/XkSNHFBQUpIyMDGufq6WlpZo8ebIOHTqk8PBwTZ8+XT/96U8D\nHcvrhivk715NLD8/X3PnztWyZcsCHatSK1as0Pr169WgQYNAR6nW+vXrFRUVpfnz5+ubb75Rv379\nrC3kTZs2SZKys7O1fft2Pfvss9Y+/mVlZZo+fXq1Z2XawO12yxhj9T8aL9i+fbs++eQTvfrqqyop\nKdGf//znQEeqUv/+/dW/f39J0lNPPaUBAwZYV8aS9N5776m8vFzZ2dnaunWrFi1apCVLlgQ6VqVW\nrVqlhg0batWqVdq/f78yMjL04osvBjqW1w13yPpqriYWaNHR0dY+sb+rV69eeuyxxySd/5xdcHBw\ngBNVrXv37srIyJAkffXVV1a+wV0wb948DRkyRP/2b/8W6CjVKiwsVElJiUaNGqXhw4crPz8/0JGq\ntGXLFsXExGjChAkaN26cunXrFuhIV7Rr1y59/vnnGjx4cKCjVKpp06aqqKiQx+ORy+Wq8toTNvj8\n88/VpUsXSVKzZs20b9++ACe6mL17zk9cLpf30JokBQcHq7y83MonUWJiog4fPhzoGFd04UPuLpdL\njz76qFJTUwOcqHohISGaNGmS/vGPf+i5554LdJxKrV27Vo0aNVLnzp31pz/9KdBxqlW/fn2NHj1a\ngwYN0sGDBzVmzBi9/fbbVr6mvv76a3311VfKzMzU4cOHNX78eL399ttWX5xo+fLlmjBhQqBjVKlh\nw4Y6cuSIfvWrX+nrr79WZmZmoCNV6ec//7k2bdqk7t27a8eOHSoqKlJFRYU1k4gbboZ8NVcTQ80d\nPXpUw4cP169//Wv16dMn0HGuaN68eXrnnXc0bdo0nTt3LtBxLrNmzRpt27ZNKSkp+uc//6lJkybp\n+PHjgY5VqaZNm6pv375yOBxq2rSpoqKirM0aFRWlTp06yel0qlmzZqpXr55OnToV6FhVOnPmjA4c\nOKB777030FGq9NJLL6lTp0565513tG7dOqWnp/vvuvrf04ABAxQeHq7k5GT94x//UMuWLa0pY+kG\nLOS2bdsqJydHkq54NTHUzIkTJzRq1Cg9/vjjGjhwYKDjVOvNN9/U8uXLJUkNGjSQw+FQUJB9L4OX\nX35ZK1euVFZWln7+859r3rx5+tGPfhToWJVavXq195vdioqK5HK5rM0aFxen999/X8YYFRUVqaSk\nRFFRUYGOVaXc3Fx17Ngx0DGqFRkZ6b3q4k033aTy8nJVVFQEOFXldu3apY4dO+rVV19Vr169dNtt\ntwU60kVuuKlhjx49tHXrVg0ZMsR7NTF8P5mZmTpz5oyWLl2qpUuXSjp/QpqNJyP17NlTkydP1rBh\nw1ReXq4pU6ZYmbMuGThwoCZPnqyhQ4fK4XBo9uzZ1h51SkhIUG5urgYOHChjjKZPn27VDOlSBw4c\nUOPGjQMdo1ojR47UlClTlJycrLKyMqWlpalhQ/98m9X31aRJEy1evFiZmZmKiIjQH/7wh0BHughX\n6gIAwAL2HasDAOAGRCEDAGABChkAAAtQyAAAWIBCBgDAAhQyAAAWoJABALAAhQwAgAX+H9bJdlbg\nI0McAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ce87f6f898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "forest = RandomForestClassifier()\n",
    "visualizer = ClassBalance(forest, classes=classes)\n",
    "\n",
    "visualizer.fit(train_images, train_labels)\n",
    "visualizer.score(test_images, test_labels)\n",
    "g = visualizer.poof()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
